|International Journal of Computer Applications
|Foundation of Computer Science (FCS), NY, USA
|Volume 100 - Number 4
|Year of Publication: 2014
|Authors: Neha Kamdar, Neeraj Paliwal
Neha Kamdar, Neeraj Paliwal . CARF-F: Conditional Active RREQ Flooding-Filter based Prevention Scheme for AODV in MANET. International Journal of Computer Applications. 100, 4 ( August 2014), 42-47. DOI=10.5120/17516-8076
Wireless network is a growing field of latest technology because of its increased popularities over the rural and urban areas. Such network provides the mobility based service usage and hence removes the location dependencies for the users of mobile devices such as laptops, cell phones, Tablets and PDA's. These networks are categorized on the basis of their infrastructural usage and range of transmissions. Mobile ad-hoc network is one of its types having infrastructure less environment performing short range communications. In this the overall responsibility of communication is shifted from networked components to mobile node itself working as a router. As the facility is increased some relaxation is also made available for malicious users and hence it is more susceptible to network attack due to its open environment and dynamically changing nature. Flooding is used for the most performed network attack aims at degrading the network performance by inserting the several dummy RREQ packets in the network. These packets are large in quantity and hence consume lots of network resources such as, bandwidth and nodes battery power. Over the last few years various approaches is been suggested to overcome flooding related issues. Even after these traditional flooding attacks solutions, there are some problems which remain unsolved like: isolation of fake RREQ from actual packets, maliciousness percentage based on nodes behaviour and previous participation, probability of malicious flooded packet detections. Thus this paper proposes a novel CARF-F based flooding attack detection and removal mechanism for AODV protocol. At the initial level of analytical results the approach is proving its strong presence in near future.